Users may watch videos using the Internet. The users may specify the video he or she intends to watch or a recommendation system may recommend videos for a user to watch. Some recommendation systems generate personalized video recommendations for each user using data that is associated with the particular user. For example, a recommendation system may provide video recommendations to a user based on the user's geographical location, gender, interests, age, etc. Some recommendation systems use a content-based approach that analyzes properties of videos that a user has selected in the past and then recommends videos with similar properties. For example, if a user has selected many videos that include dogs in the past, the user may be recommended to watch other videos classified as having dogs. However, this approach typically requires extensive history of a user's prior selection of videos.
Some recommendation systems also make recommendations based on a binary decision of whether a user has selected a video to watch or not. The recommendation systems do not treat videos that are selected and fully watched differently from videos that are selected and then watched for a short period of time. This approach may lead to video suggestions that are of little value to the user.